Four-Dimensional Trajectory Planning for Urban Air Traffic Vehicles Based on Improved RRT* Algorithm

In this paper, we propose a trajectory planning method for high-density flights in a complex environment with multiple buildings in the city. Moreover, a simulation study of four-dimensional trajectory planning for aircraft is conducted with different flight densities in an urban environment. In this paper, the Rapidly Exploring Random Tree Star (RRT
$^{\ast}$
) algorithm is improved to adapt to urban air traffic, including node expansion angle constraint, dynamic collision detection, adapting to stratified airspace, and adding virtual obstacles. The urban environment model with multiple obstacles is established, the stratified airspace and flight parameters of the vehicle are set, and simulation experiments are conducted. The experimental results demonstrate the effectiveness of the proposed algorithms and the necessity of real-time and unified management of high-density flights in urban air traffic. The proposal of maximum aircraft density and airspace layer construction in the stratified airspace of the simulation environment is obtained. Lastly, a four-dimensional trajectory planning method for high-density flights in an urban multi-building environment is provided.